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Artificial neuron

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NX-421: Neural signals and signal processing

Understanding, processing, and analysis of signals and images obtained from the central and peripheral nervous system

BIO-311: Neuroscience

The course starts with fundamentals of electrical - and chemical signaling in neurons. Students then learn how neurons in the brain receive and process sensory information, and how other neurons contr

CIVIL-226: Introduction to machine learning for engineers

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Students understand basic concepts and methods of machine learning. They can describe them in mathematical terms and can apply them to data using a high-level programming language (julia/python/R).

CS-433: Machine learning

Machine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and pr

NX-435: Systems neuroscience

The course "Systems Neuroscience" explores neural circuits and networks to understand how groups of neurons process information and generate behavior. It integrates techniques from neurophysiology, an

CS-330: Artificial intelligence

Introduction aux techniques de l'Intelligence Artificielle, complémentée par des exercices de programmation qui montrent les algorithmes et des exemples de leur application à des problèmes pratiques.

BIOENG-456: Controlling behavior in animals and robots

Students will acquire an integrative view on biological and artificial algorithms for controlling autonomous behaviors. Students will synthesize and apply this knowledge in oral presentations and comp

ME-390: Foundations of artificial intelligence

This course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanica

EE-556: Mathematics of data: from theory to computation

This course provides an overview of key advances in continuous optimization and statistical analysis for machine learning. We review recent learning formulations and models as well as their guarantees